5072 Tensorflow Jobs - Page 40

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Senior Python Developer – Client – Merck, H and M, TIAA, MINT Job Description Bachelor’s or master’s degree with 3+ years of strong Python development experience Design, develop, and maintain high-performance web applications using Python and related frameworks. Strong understanding of Python OOPs, Data type, Data Structure and algorithm , Exception handling, Decarotor , Generator, Iterator, Automation. Strong understanding of Python Libraries (Pandas, TensorFlow, Numpy, SciPy) Experience in Cloud Azure / AWS Develop, optimize, and manage complex APIs (RESTful or GraphQL). Collaborate with cross-functional teams to define, design, and ship new features. Troubleshoot and resolve advanced technical issues in development and production environments. Conduct technical evaluations of new tools and frameworks, recommending their adoption when appropriate. Stay ahead of emerging trends in Python development, ensuring the team remains at the forefront of innovation. Advanced proficiency in Python and frameworks like Django,Flask, or FastAPI. Good understanding of Database Postgres / MySQL & ORM Library i.e. SQL Alchemy/ any ORM libraries Understanding of Code Repository tools i.e. GIT , SVN Strong understanding of DevOps principles(Docker, Kubernetes and microservices) EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

About: Newton School has formed a powerful partnership to drive transformation in the world of technology and education. Newton School, dedicated to bridging the employability gap, has partnered with Rishihood University, Sonipat, India's first impact university, and Ajeenkya DY Patil University, Pune. Together, we will be revolutionizing education, empowering students, and shaping the future of technology. With a team of experienced professionals and renowned investors, we are united in our mission to solve the employability challenge and make a lasting impact on society. Key Responsibilities Teach Applied AI/ML: Design and deliver practical, project-based courses in AI/ML (e.g., Python for ML, Statistics, ML Algorithms, Deep Learning, NLP, CV, ML Ops, GenAI). Develop Industry-Relevant Curriculum: Help design and update the AI/ML curriculum to reflect current industry tools, techniques, and best practices, incorporating your own professional experience and case studies. Mentor Student Projects: Guide students through hands-on AI/ML projects, providing technical direction, code reviews, and feedback based on industry standards. Guide & Mentor Students: Advise students on developing practical skills, understanding career paths in AI/ML, and preparing for internships and job placements. Stay Current: Keep your expertise sharp on the latest AI/ML trends and technologies, bringing that knowledge into the classroom. Collaborate: Work closely with other industry-expert faculty and staff to create a unified and effective learning experience. Assess Practical Skills: Create and evaluate assignments, projects, and assessments focused on measuring practical application and understanding. Required Qualifications & Experience Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, or a similar field. (A PhD is valued but not required.) Minimum 2-5 years of direct, hands-on professional experience in the tech industry as an AI/ML Engineer, Data Scientist, Research Scientist, or similar role involving significant AI/ML development and deployment. Proven Industry Track Record: Demonstrable experience building, training, and deploying machine learning models (including deep learning) to solve real-world problems. Deep AI/ML Understanding: Strong grasp of core ML algorithms (classical & deep learning - CNNs, RNNs, Transformers), underlying theory, model evaluation, statistics, and current research/industry trends. Passion for Teaching/Mentoring: Clear ability and enthusiasm for explaining complex technical topics and guiding others. Experience in corporate training, mentoring junior team members, leading workshops, creating technical content, or supervising projects is highly relevant. (Formal academic teaching experience is not a prerequisite.) Required Skills Technical : Expert-level Python programming. Proficiency with data science libraries (Pandas, NumPy, Scikit-learn). Hands-on experience with ML/DL frameworks (TensorFlow, PyTorch). Strong SQL and data handling skills. Understanding of ML Ops practices and tools (Git, Docker, Cloud platforms - AWS/GCP/Azure). Knowledge of key AI areas (NLP, Computer Vision, Generative AI/LLMs). Communication: Excellent ability to explain technical concepts clearly to students. Strong mentoring skills. Collaboration: Team-oriented approach. Passion: Genuine interest in education and student success within an innovative, practical learning environment. Good-to-Have Prior teaching experience at the undergraduate or graduate level. Familiarity with modern teaching methodologies and academic tools. Perks & Benefits Competitive salary packages aligned with industry standards. Access to state-of-the-art labs and classroom facilities. Contribution to cutting-edge academic work in collaboration with the Newton School of Technology and Rishihood University.

We are seeking a highly skilled Machine Learning Lead to drive the development and deployment of advanced machine learning solutions across our products and platforms. This role demands a balance of technical excellence, project leadership, and a deep understanding of business goals. You will lead a team of ML engineers and data scientists, collaborating cross-functionally with product, engineering, and business stakeholders to deliver impactful AI-driven outcomes. Roles and Responsibilities Key Responsibilities: Lead End-to-End ML Projects: Own the full lifecycle of ML solutions from problem scoping, data exploration, model development, deployment, and post-deployment monitoring. Own the Gen AI Strategy: Define and drive the technical vision and execution strategy for Gen AI use cases across the organization. Architect Scalable Solutions: Design robust ML systems and pipelines that integrate seamlessly into production environments. Team Leadership: Mentor and guide a team of ML engineers and data scientists, fostering a culture of technical excellence, innovation, and continuous learning. Modeling & Research: Stay up to date with the latest advancements in ML/AI and guide experimentation with novel algorithms (e.g., deep learning, NLP, GenAI, reinforcement learning). Build RAG & Prompt Engineering Pipelines: Design scalable architectures for RAG, vector search, prompt tuning, and prompt chaining with tools like LangChain, LlamaIndex, and FAISS. Stakeholder Collaboration: Work closely with product managers, engineers, and domain experts to translate business problems into technical solutions. Operationalize ML: Partner with MLOps/DevOps teams to deploy, monitor, and maintain ML models in production, ensuring reliability and scalability. Must-Have: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field (PhD is a plus). 8+ years of hands-on experience in machine learning, with at least 1–2 years in a leadership or mentorship role. Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, HuggingFace Transformers, etc. Strong understanding of statistics, optimization, and model evaluation techniques. Experience with cloud platforms (AWS, GCP, or Azure) and tools like Docker, Kubernetes, MLflow, or Kubeflow. Proficiency in Python and Gen AI frameworks such as LangChain, Crew AI, or similar. Proven track record of deploying ML models into production at scale. Excellent communication and leadership skills. Nice-to-Have: Background in domain-specific ML (e.g., healthcare, fintech, manufacturing). Familiarity with data engineering tools like Apache Spark, Airflow. Prior experience in startup or fast-paced environments. Skills to Have : Artificial Intelligence, Natural Language Processing, machine learning, Deep Learning, Scikit-Learn, Python, Pytorch, Tensorflow, data science, Huggingface, Transformers, Langchain, Crew AI, Aws Cloud, Gcp Cloud, Azure Cloud.

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Years of Experience: Candidates with 4+ years of hands on experience PwC US - Acceleration Center is seeking a highly skilled and experienced GenAI Data Scientist to join our team at Senior Associate level. As a GenAI Data Scientist, you will play a critical role in developing and implementing machine learning models and algorithms for our GenAI projects. The ideal candidate should have a strong background in data science, with a focus on GenAI technologies, and possess a solid understanding of statistical analysis, machine learning, data visualization, and application programming. Responsibilities Collaborate with cross-functional teams to understand business requirements and identify opportunities for applying GenAI technologies. Develop and implement machine learning models and algorithms for GenAI projects. Perform data cleaning, preprocessing, and feature engineering to prepare data for analysis. Collaborate with data engineers to ensure efficient data processing and integration into machine learning pipelines. Validate and evaluate model performance using appropriate metrics and techniques. Develop and deploy production-ready machine learning applications and solutions. Utilize object-oriented programming skills to build robust and scalable software components. Utilize Kubernetes for container orchestration and deployment. Design and build chatbots using GenAI technologies. Communicate findings and insights to stakeholders through data visualizations, reports, and presentations. Stay up-to-date with the latest advancements in GenAI technologies and recommend innovative solutions to enhance data science processes. Requirements Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. 3-5 years of relevant technical/technology experience, with a focus on GenAI projects. Strong programming skills in languages such as Python, R, or Scala. Proficiency in machine learning libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn. Experience with data preprocessing, feature engineering, and data wrangling techniques. Solid understanding of statistical analysis, hypothesis testing, and experimental design. Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud. Knowledge of data visualization tools and techniques. Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Ability to work in a fast-paced and dynamic environment. Preferred Qualifications Experience with object-oriented programming languages such as Java, C++, or C#. Experience with developing and deploying machine learning applications in production environments. Understanding of data privacy and compliance regulations. Relevant certifications in data science or GenAI technologies. Nice To Have Skills Experience with Azure AI Search, Azure Doc Intelligence, Azure OpenAI, AWS Textract, AWS Open Search, AWS Bedrock. Familiarity with LLM backed agent frameworks such as Autogen, Langchain, Semantic Kernel, etc. Experience in chatbot design and development. Professional And Educational Background BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA

Description About Amazon.com: Amazon.com strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon.com continues to grow and evolve as a world-class e-commerce platform. Amazon's evolution from Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company's DNA. The world's brightest technology minds come to Amazon.com to research and develop technology that improves the lives of shoppers and sellers around the world. Overview of the role The Business research Analyst will be responsible for data and Machine learning part of continuous improvement projects across compatibility and basket building space. This will require collaboration with local and global teams, which have process and technical expertise. Therefore, RA should be a self-starter who is passionate about discovering and solving complicated problems, learning complex systems, working with numbers, and organizing and communicating data and reports. In compatibility program, RA perform Big data analysis to identify patterns, train model to generate product to product relationship and product to brand & model relationship. RA also continuously improve the ML solution for higher solution accuracy, efficiency and scalability. RA should writes clear and detailed functional specifications based on business requirements as well as writes and reviews business cases. Key job responsibilities Scoping, driving and delivering complex projects across multiple teams. Performs root cause analysis by understand the data need, get data / pull the data and analyze it to form the hypothesis and validate it using data. Conducting a thorough analysis of large datasets to identify patterns, trends, and insights that can inform the development of NLP applications. Developing and implementing machine learning models and deep learning architectures to improve NLP systems. Designing and implementing core NLP tasks such as named entity recognition, classification and part-of-speech tagging. Dive deep to drive product pilots, build and analyze large data sets, and construct problem hypotheses that help steer the product feature roadmap (e.g. with use of Python), tools for database (e.g. SQL, spark) and ML platform (tensorflow, pytorch) Conducting regular code reviews and implementing quality assurance processes to maintain high standards of code quality and performance optimization. Providing technical guidance and mentorship to junior team members and collaborating with external partners to integrate cutting-edge technologies. Find the scalable solution for business problem by executing pilots and build Deterministic and ML model (plug and play on readymade ML models and python skills). Performs supporting research, conduct analysis of the bigger part of the projects and effectively interpret reports to identify opportunities, optimize processes, and implement changes within their part of project. Coordinates design effort between internal team and external team to develop optimal solutions for their part of project for Amazon’s network. Ability to convince and interact with stakeholders at all level either to gather data and information or to execute and implement according to the plan. About The Team Amazon.com operates in a virtual, global eCommerce environment without boundaries, and operates a diverse set of businesses in 14 countries, including Retail, third party marketplaces, eCommerce platforms, web services for developers. Retail Business Service (RBS) organization is a core part of leading customer experience and selling partners experience optimization. This team is part of RBS Customer Experience business unit. The team’s primary role is to create and enhance retail selection on the worldwide Amazon online catalog. The compatibility program handled by this team has a direct impact on customer buying decisions and online user experience. Compatibility program aims to address Customer purchase questions if two products works together, as well as reduce return due to incompatibility. Basic Qualifications Basic Qualifications Ability to analyse and then articulate business issues to a wide range of audiences using strong data, written and verbal communication skills Good mastery of BERT and other NLP frameworks such as GPT-2, XLNet, and Transformer models Experience in NLP techniques such as tokenization, parsing, lexing, named entity recognition, sentiment analysis and spellchecking Strong problem-solving skills, creativity and ability to overcome challenges SQL/ETL, Automation Tools Relevant bachelor’s degree or higher 3+ years combined of relevant work experience in a related field/s (project management, customer advocate, product owner, engineering, business analysis) - Diverse experience will be favored eg. a mix of experience across different roles Be self motivated and autonomous with an ability to prioritize well, and remain focused when working within a team located in across several countries and time zones Preferred Qualifications Preferred Qualifications 3+ years combined of relevant work experience in a related field/s (project management, customer advocate, product owner, engineering, business analysis) - Diverse experience will be favored eg. a mix of experience across different roles Understanding of machine learning concepts including developing models and tuning the hyper-parameters, as well as deploying models and building ML service Experience with computer vision algorithms and libraries such as OpenCV, TensorFlow, Caffe or PyTorch. Technical expertise, experience in Data science and ML Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - ADCI - BLR 14 SEZ Job ID: A2896681

Who are we and what do we do? InMobi Group’s mission is to power intelligent, mobile-first experiences for enterprises and consumers. Its businesses across advertising, marketing, data and content platforms are shaping consumer experience in a world of connected devices. InMobi Group has been recognized on both the 2018 and 2019 CNBC Disruptor 50 list and as one of Fast Company’s 2018 World’s Most Innovative Companies. Consistently featured among the “Great Places to Work” in India since 2017, our culture is our true north, enabling us to think big, solve complex challenges and grow with new opportunities. InMobians are passionate and driven, creative and fun-loving, take ownership and are outcome-driven. We invite you to join our tribe as we dream big and chase your passion. About AI Engineering Director - Enterprise Digital & AI transformation across Inmobi is underway for - unlocking productivity & realizing efficiencies across the business, streamlining critical process flows and integrating cross-system architecture to achieve a lean and agile organizational set up. This involves a strong understanding of the company’s underlying business, system and process challenges, translating them into long term sustainable solutions that are applicable across InMobi’s expanding business units. This team works across a spectrum of enterprise systems and products building end-to-end features and capabilities that help establish a fully integrated blueprint of the company’s data architecture and system landscape. The Enterprise systems span the end-to-end value chain covering Lead generation, Sales & CRM, Order fulfilment, Service, Financial systems, BI Dashboards and NLP based Analytics. Reporting to the Chief Digital Officer , this person will lead a team of engineers and collaborate deeply with Product managers, Designers and other Engineering teams, to build AI solutions grounded in consistent architectures and incorporates ongoing advancements. These AI solutions will help in Sales & Marketing transformation, Finance transformation, Service & Operational processes transformation. Are you interested in shaping the era of AI, especially in an Enterprise context and scale? This role requires curiosity to understand the quickly growing AI landscape, continuous disruptive changes, knowledge in modern coding languages, different platforms (esp GCP/ Azure/ Salesforce), Machine Learning and LLMs. As the Enterprise AI Engineering Leader, you are the face of the Enterprise AI engineering team, representing their work, and unblocking the team when problems arise. You manage a highly skilled team and help in the growth of their careers. You drive action and alignment by cultivating relationships with senior management and partnerships with product management and design leaders. You bring a deep understanding and expertise in digital transformation opportunities across AI, supported by thought leadership in technologies such as Generative AI, Advanced Analytics and App Modernization. What you’ll do: Partner with the Enterprise Product team and all concerned stakeholders to understand business needs and translate them into technical requirements and solutions. Lead the development, deployment, and optimization of AI (GenAI) Solutions, Tools, frameworks in the Enterprise space for core business process areas. In this role, you will work closely with cross-functional teams, bringing technical expertise and hands-on problem-solving to ensure the successful delivery of AI solutions that support our business objectives (in the broad process areas described earlier) Support POCs/ Pilots projects to explore and validate the ever-evolving AI technologies and solutions. Stay updated regarding LLMs, MCP, A2A, ADK, Agentic AI landscape and the fast- changing AI technology & solution landscape - ensuring the innovations drive impact. Participating in the full AI development lifecycle, including data preparation, design, coding, testing, deployment, and support. Continuously assess and optimize software architecture, focusing on scalability, reliability, and alignment with emerging trends. Document designs, development processes, and best practices to promote knowledge sharing. Mentor and enable career growth for your team. Support upskilling and re-skilling of other Engineering team members + business users. What you are good at Supporting the development/ adoption/ optimization of AI-driven applications to meet organizational needs. Solving technical challenges and developing scalable, innovative solutions. Applying Change Management principles to ensure successful technology rollouts. Proactively identifying and implementing automation/ AI capabilities – in an Enterprise setup. Collaborating effectively with diverse stakeholders, including technical teams and business leaders. Adapting to fast-paced environments and evolving priorities with high energy and autonomy. Leveraging expertise in (Gen) AI solutions, Technologies & frameworks as listed above and enabling underlying system Integrations/ Infrastructure to deliver impactful solutions. Demonstrate strong problem-solving and analytical skills. Excellent documentation and presentation skills for technical and non-technical audiences. What You'll Bring A bachelor’s degree in Computer Science, Engineering, or a related field. Advanced degrees in AI and Data Science are a plus. 10 - 12 years of professional experience in Engineering/ Software development with increasing responsibility. At least 4 – 5 years proven experience in implementing AI-driven applications. Experience in developing and deploying machine learning models and AI solutions. At least a few of the following : Statistics and Probability Theory, Regression Modelling, Clustering Methods, Deep Learning, Neural Networks, Natural Language Processing, Text Mining, Computer Vision, Image Recognition, Time Series Forecasting, Machine Learning Visualization Tools, Tree Ensembles Proficiency in programming languages like Python, R, or Java. Familiarity with AI and machine learning frameworks (e.g., TensorFlow, PyTorch). Experience on big data technologies and tools (e.g., Hadoop, Spark). At least 2 years in Gen AI/ LLM based solutions. GCP/ Azure/ Salesforce / other platforms - Data and AI services, Data Engineering, Analytics, Machine Learning, Cognitive Services; Cognitive Search and exposure to OpenAI solutions. Previous experience building a user-facing (Gen)AI/ LLM software applications Knowledge of LLMs, RAG/Agentic - Architecture, core concepts and fundamentals Knowledge of evolving protocols like MCP/ A2A/ ADK and others. Strong technical proficiency in both frontend and backend development (e.g., React, Python, Java, Typescript). Experience with design engineering, customer workshops, defining clear problem statements. Demonstrated ability to work with complex datasets and perform data preprocessing and analysis. Expertise needed in other areas - Experience with code repositories including but not limited: Azure DevOps; GitHub as well as understanding of branching and tagging strategies; understanding of Continuous Integration/Continuous Deployment (CI/CD) pipelines. Experience with cloud technologies and infrastructure as code (e.g., AWS, Kubernetes, Terraform). Familiarity with software design patterns, architecture trade-offs, and integration best practices. Knowledge of DevOps practices, CI/CD pipelines, and automated testing frameworks. Experience with database management and data processing.

This role is for one of Weekday's clients Salary range: Rs 1000000 - Rs 2000000 (ie INR 10-20 LPA) Min Experience: 5 years Location: Pune, Bengaluru JobType: full-time Requirements About the Role: We are seeking a highly skilled and innovative Senior Data Scientist to join our advanced analytics team. In this role, you will leverage your expertise in Python , Natural Language Processing (NLP) , and Large Language Models (LLMs) to build, deploy, and optimize AI-powered solutions that drive business insights and improve product functionality. You will work closely with cross-functional teams, including engineering, product, and domain experts, to translate complex business challenges into robust machine learning models. This is a high-impact role for someone who thrives in a data-driven environment and is passionate about solving real-world problems through intelligent systems and cutting-edge data science techniques. Key Responsibilities: Design, develop, and deploy scalable data science solutions, focusing on natural language processing (NLP) and large language models (LLMs). Apply machine learning and deep learning algorithms to extract insights from structured and unstructured datasets. Develop custom NLP pipelines for tasks such as sentiment analysis, topic modeling, named entity recognition, and text summarization. Fine-tune, evaluate, and deploy LLMs like GPT, BERT, or similar to solve domain-specific problems. Collaborate with data engineers to build and maintain robust data pipelines for training and production environments. Work with product and business teams to identify opportunities where data science can deliver business value. Communicate technical findings and insights to non-technical stakeholders in a clear and actionable manner. Stay up-to-date with the latest advancements in AI/ML, NLP, and LLM research and apply relevant techniques to ongoing projects. Lead and mentor junior data scientists in best practices for model development, validation, and deployment. Required Skills & Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. PhD preferred. Minimum of 5 years of hands-on experience in data science or applied machine learning. Strong proficiency in Python and related libraries such as NumPy, pandas, scikit-learn, TensorFlow, PyTorch, and spaCy. Demonstrated experience in NLP techniques and language model fine-tuning, including experience with Hugging Face Transformers or OpenAI APIs. Solid understanding of machine learning theory, model evaluation, and feature engineering. Experience working with cloud platforms such as AWS, GCP, or Azure for scalable model deployment. Familiarity with version control (Git), collaborative workflows, and agile development. Excellent communication skills with the ability to present complex technical concepts to diverse audiences. Strong analytical mindset with a focus on delivering measurable business outcomes. Nice to Have: Experience with vector databases (e.g., FAISS, Pinecone) and semantic search implementations. Familiarity with LLMOps, prompt engineering, and conversational AI systems. Experience in deploying and maintaining ML models in production environments

Gen AI - Artificial Intelligence Specialist Work Location: Hyderabad - Work from Office(Must) Willing to Join - ASAP Responsibilities - Drive customer conversations for Gen AI opportunities Understand customer specific requirements and create customer acceptable Gen AI solution architectures Create customer proposals and RFP responses Guide solution engineers in creating Gen AI POC and solutions for industry verticals Show initiative and drive topics to resolution in an elevated level of quality, speed, reliability, and efficiency Staying abreast of the latest developments in technology and industry, best practices and finding where they can be incorporated Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, proving the potential of Generative AI applications Qualifications - Experience in software development: 8+ years Experience in Generative AI solution development: 3 years Bachelor’s degree or above in Computer Science, Software Engineering or similar disciplines Experience in two industry domains and ability to learn new domains quickly Adept at critical thinking and logical reasoning for problem-solving Be good at teamwork and delivering under pressure Generative AI oriented Experience with at least one cloud technology: Azure, AWS, GCP Good understanding of NVIDIA or other similar technologies Understanding of sound design principles and patterns Solid appreciation of AI/ML concepts Required Skills - Extremely dynamic and enthusiastic about technology Development experience with one or more of these technologies: C++, Java, JavaScript, HTML, C#, Python, node.js Be able to adapt quickly to new challenges and an evolving technology stack Excellent written and verbal communication skills. Fluent English is essential Strong analytical and critical thinking skills Demonstrating a customer-focused attitude; Excellent communication skills (listening, presenting, writing, formal and informal) Initiative-taking, self-driven, curious, open-minded, resourceful, and flexible with the ability to learn quickly Firsthand of Python, ML Algorithms and Statistics Knowledge of source code maintenance and versioning tools Strong in Object Oriented Programming Concepts Good in debugging and analytical skills Preferred Skills - 5+ years of experience in ML development and MLOps Strong programming skills, with ability in languages like Python, with a good knowledge of ML, Data and API libraries Expertise in creating end-to-end data pipelines (sourcing, exploration, automation, etc.) Experience with ML models and their development Should know ModelOps/MLOps, AutoML, AI Ethics, Trust and Explainable Aí Understanding of some of the popular ML frameworks such as SparkML, TensorFlow, scikit-learn, XGBoost, H2O, etc. Experience working in a cloud environment (AWS, Azure, GCP) or a containerised environment (Mesos, Kubernetes) Interest in understanding functional and industry business challenges Desirable to know about IT Industry and potential GenAI use case in insurance processes Ideally, you’ll also have Expertise in Big Data, Data Modelling

About Darwinbox We’re designing the future of work by building the world's best HR tech, driven by a fierce focus on employee experience and customer success, and continuous, iterative innovation. Founded in 2015, we now serve 1.5M+ employees in 650+ enterprises, and that includes massive conglomerates to unicorn startups, like Makemytrip, JSW, Vedanta, Mahindra, and Kotak, plus leading global brands like Nivea, Starbucks, Sephora, AXA, Cigna, T-Systems, and Calvin Klein. We’re backed by marquee investors like TCV, Salesforce, Sequoia, Lightspeed Ventures, and others. Most importantly, we’re growing at a phenomenal pace, and that means exponential growth and learning opportunities for you, plus a band of passionate and fun people to work with within a place where your ideas take precedence over your designation. Why Join Us? The rate at which our product and market presence are growing is unprecedented. We’re a Rocketship. We’re not planning on slowing down anytime soon. And, that’s why we need you! You’ll experience a culture of: Disproportionate Rewards for top performance Accelerated Growth in a hyper-growth environment Wellbeing First culture focused on employee care Continuous Learning and Professional Development Meaningful Relationships and a Collaborative Environment Role Overview We are seeking an experienced AI Architect to lead the development of our AI and Machine Learning infrastructure and specialized language models for HR applications. This role will establish and lead our MLOps practices and drive the creation of scalable, production-ready AI/ML systems. Key Responsibilities Discuss the feasibility of AI/ML use cases along with architectural design with business teams, and translate the vision of business leaders into a realistic technical implementation Play a key role in defining the AI architecture and selecting appropriate technologies from a pool of open-source and commercial offerings Design and implement robust ML infrastructure and deployment pipelines Establish comprehensive MLOps practices for model training, versioning, and deployment Lead the development of HR-specialized language models (SLMs) Implement model monitoring, observability, and performance optimization frameworks Develop and execute fine-tuning strategies for large language models Create and maintain data quality assessment and validation processes Design model versioning systems and A/B testing frameworks Define technical standards and best practices for AI development Optimize infrastructure for cost, performance, and scalability Required Qualifications 7+ years of experience in ML/AI engineering or related technical roles 3+ years of hands-on experience with MLOps and production ML systems Demonstrated expertise in fine-tuning and adapting foundation models Strong knowledge of model serving infrastructure and orchestration Proficiency with MLOps tools (MLflow, Kubeflow, Weights & Biases, etc.) Experience implementing model versioning and A/B testing frameworks Strong background in data quality methodologies for ML training Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face) Experience with cloud-based ML platforms (AWS, Azure, Google Cloud) Proven track record of deploying ML models at scale Preferred Qualifications Experience developing AI applications for enterprise software domains Knowledge of distributed training techniques and infrastructure Experience with retrieval-augmented generation (RAG) systems Familiarity with vector databases (Pinecone, Weaviate, Milvus) Understanding of responsible AI practices and bias mitigation Bachelor's or Master's degree in Computer Science, Machine Learning, or related field What We Offer Opportunity to shape AI strategy for a fast-growing HR technology leader Collaborative environment focused on innovation and impact Competitive compensation package Professional development opportunities Flexible work arrangements Qualified candidates who are passionate about applying cutting-edge AI to transform HR technology are encouraged to apply.

About the Role As a Principal Data Scientist in our AdTech team, youll drive innovation in our advertising platform using advanced machine learning and statistical methods. Youll tackle complex problems in real-time bidding, ad ranking optimization, budget efficiency, and performance measurement that directly impact our businesss bottom line. This role requires technical excellence and business acumen and youll collaborate with cross-functional teams to transform data insights into actionable strategies that enhance our advertising ecosystem. What you will do Design and develop sophisticated bidding, budget pacing and other algorithms that optimize ad spend or ROI. Create frameworks and experimental design to measure ad effectiveness and ROI. Collaborate with product and engineering teams to translate business requirements into efficient AI/ML solutions. Communicate long-term roadmap, insights and recommendations to tech and business leadership. Mentor junior data scientists and provide technical Lead research initiatives in machine learning, auction theory and advertising technology. What you will need B.Tech in Computer Science, Machine Learning, or a related field with at least 6+ years of experience in AI/ML research. Experience in auction theory, predictive modelling, causal inference, and reinforcement learning. Expertise in PyTorch or TensorFlow, and proficiency in Python as well as big data technologies. History of mentoring junior data scientists, and comfortable in driving multiple problem statements. Excellent communication skills, able to explain complex concepts to both technical and non-technical audiences. Preferred Qualifications: M.Tech or Ph.d in Computer Science with a specialization in Machine Learning. 3+ years of experience applying machine learning and statistical modeling in AdTech, or related domains. Exposure in real-time bidding systems, programmatic advertising, or ad exchanges. Track record of successful research-to-product transitions. Strong publication record in top AI conferences (e.g., NeurIPS, ICML, ICLR, KDD, CVPR, AAAI).

Who We Are Ema is building the next generation AI technology to empower every employee in the enterprise to be their most creative and productive. Our proprietary tech allows enterprises to delegate most repetitive tasks to Ema, the AI employee. We are founded by ex-Google, Coinbase, Okta executives and serial entrepreneurs. We’ve raised capital from notable investors such as Accel Partners, Naspers, Section32 and a host of prominent Silicon Valley Angels including Sheryl Sandberg (Facebook/Google), Divesh Makan (Iconiq Capital), Jerry Yang (Yahoo), Dustin Moskovitz (Facebook/Asana), David Baszucki (Roblox CEO) and Gokul Rajaram (Doordash, Square, Google). Our team is a powerhouse of talent, comprising engineers from leading tech companies like Google, Microsoft Research, Facebook, Square/Block, and Coinbase. All our team members hail from top-tier educational institutions such as Stanford, MIT, UC Berkeley, CMU and Indian Institute of Technology. We’re well funded by the top investors and angels in the world. Ema is based in Silicon Valley and Bangalore, India. This will be a hybrid role where we expect employees to work from office three days a week. Who You Are We're looking for an innovative and passionate Machine Learning Engineers to join our team. You are someone who loves solving complex problems, enjoys the challenges of working with huge data sets, and has a knack for turning theoretical concepts into practical, scalable solutions. You are a strong team player but also thrive in autonomous environments where your ideas can make a significant impact. You love utilizing machine learning techniques to push the boundaries of what is possible within the realm of Natural Language Processing, Information Retrieval and related Machine Learning technologies. Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You Will Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems. Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems. Lead the processing and analysis of large, complex datasets (structured, semi-structured, and unstructured), and use your findings to inform the development of our models. Work across the complete lifecycle of ML model development, including problem definition, data exploration, feature engineering, model training, validation, and deployment. Implement A/B testing and other statistical methods to validate the effectiveness of models. Ensure the integrity and robustness of ML solutions by developing automated testing and validation processes. Clearly communicate the technical workings and benefits of ML models to both technical and non-technical stakeholders, facilitating understanding and adoption. Ideally, You'd Have A Master’s degree or Ph.D. in Computer Science, Machine Learning, or a related quantitative field. Proven industry experience in building and deploying production-level machine learning models. Deep understanding and practical experience with NLP techniques and frameworks, including training and inference of large language models. Deep understanding of any of retrieval, ranking, reinforcement learning, and agent-based systems and experience in how to build them for large systems. Proficiency in Python and experience with ML libraries such as TensorFlow or PyTorch. Excellent skills in data processing (SQL, ETL, data warehousing) and experience working with large-scale data systems. Experience with machine learning model lifecycle management tools, and an understanding of MLOps principles and best practices. Familiarity with cloud platforms like GCP or Azure. Familiarity with the latest industry and academic trends in machine learning and AI, and the ability to apply this knowledge to practical projects. Good understanding of software development principles, data structures, and algorithms. Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking. The ability to work collaboratively in an extremely fast-paced, startup environment. Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or genetics.

Job Description 15–20 years of overall experience with at least 4+ years in applied AI, machine learning, and statistical modeling. Design, develop, and deploy advanced generative AI models with Deep knowledge of ML/DL algorithms: Decision Trees, Random Forests, K-Means, RNN, CNN, Transformers, etc. Lead the development and implementation of large language models (LLMs) and agentic frameworks. Expertise in Python and related ML frameworks like TensorFlow, PyTorch, or Keras. Proficiency in statistics, probability, operations research, and optimization techniques. Experience in deploying AI models on cloud platforms (AWS, Azure, or GCP), including containerization and orchestration. Familiarity with LLM ecosystems and agentic frameworks like CrewAI or Autogen. Skills Required RoleAI/ML - Leader Industry TypeITES/BPO/KPO Functional AreaITES/BPO/Customer Service Required Education Bachelor Employment TypeFull Time, Permanent Key Skills AI ML DEVELOPER ARCHITECT GENERATIVE AI AND AGENTIC AI Other Information Job CodeGO/JC/419/2025 Recruiter NameMaheshwari Balasubramanian

We are looking for a skilled and creative Generative AI Engineer with 2 to 3 years of experience to join our AI/ML team. You will work on designing, fine-tuning, and deploying generative models (text, image, audio, or multi-modal) that power next-gen AI applications across business verticals. This is a hands-on role requiring a solid understanding of deep learning, model training/inference pipelines, and deployment best practices. Key Responsibilities • Build and fine-tune generative models using transformer architectures (e.g., GPT, LLaMA, T5, BERT) and diffusion models (e.g., Stable Diffusion). • Integrate LLMs into production workflows using APIs or custom backends. • Design and implement Retrieval-Augmented Generation (RAG) systems using vector databases like FAISS, Qdrant, or Pinecone. • Optimize prompt engineering and chain-of-thought logic for domain-specific tasks. • Evaluate model outputs for accuracy, relevance, hallucination rate, and latency. • Collaborate with product and engineering teams to turn prototypes into scalable systems. • Contribute to model monitoring, drift detection, and feedback loops for continual improvement. Required Skills • 23 years of experience working with machine learning models, with a focus on generative AI. • Proficient in Python and libraries such as PyTorch, TensorFlow, Transformers (Hugging Face). • Hands-on experience with OpenAI API, LangChain, or LlamaIndex. • Familiarity with vector databases (FAISS, Qdrant, Pinecone) and embedding models. • Strong understanding of LLM behavior, including prompt design, token limits, and context handling. • Experience deploying models using FastAPI, Docker, and cloud platforms (AWS, GCP, or Azure). • Good grasp of model evaluation, explainability, and safety techniques. Preferred Qualifications • Experience with multimodal AI (e.g., text-to-image, text-to-audio). • Exposure to MLOps workflows, CI/CD for ML pipelines. • Contributions to open-source AI projects or research papers. • Knowledge of privacy-preserving AI, RLHF, or federated learning is a plus.

Your Team Responsibilities Development of Scalable and Efficient AI-Driven Solutions Create AI solutions that address complex business challenges. Ensure solutions are scalable to handle large data volumes and efficient in performance. Development and Maintenance of Index Data Platforms Build and sustain platforms that generate and manage Index data. Integrate data from various sources, maintain data accuracy, and ensure reliability. Development of Data Science-Based Solutions for Quality Check of Data Points Ensure the accuracy and reliability of delivered data through advanced data science techniques. Implement metrics, detect anomalies, and validate data points to maintain high data quality. Your Key Responsibilities2. Development of AI and Data Science-Based Solutions for Quality Check of Data Points delivered to downstream Development of Scalable and Efficient AI-Driven Solutions Create AI/ML solutions that address complex business challenges. Understand business use cases and identify where and how AI can add value. Design, train, and validate machine learning models tailored to specific business needs. Design solutions leveraging generative AI and LLM. Build cost effective,scalable and high quality data solutions which will be used for critical Index products Ensure solutions can handle large volumes of data and scale with business growth. Optimize models and algorithms for performance and resource utilization. Ensure the accuracy and reliability of data through advanced data science techniques. Define and implement metrics to assess data quality. Develop models to detect anomalies and inconsistencies in data. Create automated processes to validate data points against predefined standards. Continuously refine quality check methods based on feedback and new insights. Your Skills And Experience That Will Help You Excel Artificial Intelligence (AI) and Machine Learning (ML) Understanding of machine learning algorithms, deep learning, neural networks, and reinforcement learning. Understanding and experience on Generative AI. Proficiency in working with large language models like GEMINI,GPT, BERT, and their variants. Experience in fine-tuning and deploying these models for various applications. Familiarity with frameworks like TensorFlow, PyTorch, and Keras. Programming Languages Python: Proficiency in Python for data manipulation, model development, and automation. Experience with libraries such as NumPy, pandas, scikit-learn, and matplotlib. Java (Good to have) : Strong skills in Java for building scalable and efficient applications. Knowledge of Java frameworks like Spring. Oracle (Good to have): Expertise in Oracle databases, including SQL and PL/SQL. Experience in database design, optimization, and management. Data Enginering and Cloud Solutions Proficiency in cloud platforms like Azure or Google Cloud. Leveraging cloud services for flexibility, scalability, and cost-efficiency Experience with data warehousing solutions and other cloud based data storage solutions Experience in Kubernetes and service or event driven architectures About MSCI What we offer you Transparent compensation schemes and comprehensive employee benefits, tailored to your location, ensuring your financial security, health, and overall wellbeing. Flexible working arrangements, advanced technology, and collaborative workspaces. A culture of high performance and innovation where we experiment with new ideas and take responsibility for achieving results. A global network of talented colleagues, who inspire, support, and share their expertise to innovate and deliver for our clients. Global Orientation program to kickstart your journey, followed by access to our Learning@MSCI platform, LinkedIn Learning Pro and tailored learning opportunities for ongoing skills development. Multi-directional career paths that offer professional growth and development through new challenges, internal mobility and expanded roles. We actively nurture an environment that builds a sense of inclusion belonging and connection, including eight Employee Resource Groups. All Abilities, Asian Support Network, Black Leadership Network, Climate Action Network, Hola! MSCI, Pride & Allies, Women in Tech, and Women’s Leadership Forum. At MSCI we are passionate about what we do, and we are inspired by our purpose – to power better investment decisions. You’ll be part of an industry-leading network of creative, curious, and entrepreneurial pioneers. This is a space where you can challenge yourself, set new standards and perform beyond expectations for yourself, our clients, and our industry. MSCI is a leading provider of critical decision support tools and services for the global investment community. With over 50 years of expertise in research, data, and technology, we power better investment decisions by enabling clients to understand and analyze key drivers of risk and return and confidently build more effective portfolios. We create industry-leading research-enhanced solutions that clients use to gain insight into and improve transparency across the investment process. MSCI Inc. is an equal opportunity employer. It is the policy of the firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, gender, gender identity, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy (including unlawful discrimination on the basis of a legally protected parental leave), veteran status, or any other characteristic protected by law. MSCI is also committed to working with and providing reasonable accommodations to individuals with disabilities. If you are an individual with a disability and would like to request a reasonable accommodation for any part of the application process, please email Disability.Assistance@msci.com and indicate the specifics of the assistance needed. Please note, this e-mail is intended only for individuals who are requesting a reasonable workplace accommodation; it is not intended for other inquiries. To all recruitment agencies MSCI does not accept unsolicited CVs/Resumes. Please do not forward CVs/Resumes to any MSCI employee, location, or website. MSCI is not responsible for any fees related to unsolicited CVs/Resumes. Note on recruitment scams We are aware of recruitment scams where fraudsters impersonating MSCI personnel may try and elicit personal information from job seekers. Read our full note on careers.msci.com

We are on the hunt for a Lead Artificial Intelligence (AI) passionate about architecting, developing, and supporting advanced AI computing resources and AI-enabled services. The ideal candidate will lead the charge in implementing scalable, high-performance computing infrastructures for AI/ML, collaborating with cross-functional teams to bring innovative AI solutions from conception to deployment. Roles & Responsibilities Architect, design, and implement scalable AI/ML computing infrastructures and application stacks. Collaborate with project managers, analyst & business stakeholders to design and deploy AI solutions. Develop and demonstrate AI use-cases, conducting training sessions to foster AI adoption. Evaluate and implement best practices in AI/ML and analytics. Document architecture roadmaps, reference architectures, and standard operating procedures for AI solutions. Provide expert consultation on AI-related standards, best practices, and governance frameworks. Lead disaster recovery and business continuity planning for AI computing infrastructure. Stay updated with emerging technologies in AI and ML to enhance institutional capabilities. Eligibility Criteria Master’s degree in Computer Science or Data Science or Information Technology, 6+ years in high-level architecture design and solution development for large-scale AI/ML systems. Extensive experience with deep learning frameworks (e.g., TensorFlow, Keras, PyTorch), time series analysis, predictive modelling, and NLP. Preferred Skillsets Expertise in predictive analytics, machine learning, deep learning architectures, and text analytics with NLP. Proficiency in Python for AI/ML; experience with graph databases, neural networks, and MLOps. Knowledge of high-performance AI computing platforms, Linux, and shell scripting in AI computing environments. Exceptional communication skills to articulate technical solutions to both technical and non-technical audiences. Strategic thinking in systems capacity planning, hardware and software updates, and migration.

This role is for one of Weekday's clients Salary range: Rs 1000000 - Rs 2000000 (ie INR 10-20 LPA) Min Experience: 5 years Location: Pune, Bengaluru JobType: full-time Requirements About the Role: We are seeking a highly skilled and innovative Senior Data Scientist to join our advanced analytics team. In this role, you will leverage your expertise in Python , Natural Language Processing (NLP) , and Large Language Models (LLMs) to build, deploy, and optimize AI-powered solutions that drive business insights and improve product functionality. You will work closely with cross-functional teams, including engineering, product, and domain experts, to translate complex business challenges into robust machine learning models. This is a high-impact role for someone who thrives in a data-driven environment and is passionate about solving real-world problems through intelligent systems and cutting-edge data science techniques. Key Responsibilities: Design, develop, and deploy scalable data science solutions, focusing on natural language processing (NLP) and large language models (LLMs). Apply machine learning and deep learning algorithms to extract insights from structured and unstructured datasets. Develop custom NLP pipelines for tasks such as sentiment analysis, topic modeling, named entity recognition, and text summarization. Fine-tune, evaluate, and deploy LLMs like GPT, BERT, or similar to solve domain-specific problems. Collaborate with data engineers to build and maintain robust data pipelines for training and production environments. Work with product and business teams to identify opportunities where data science can deliver business value. Communicate technical findings and insights to non-technical stakeholders in a clear and actionable manner. Stay up-to-date with the latest advancements in AI/ML, NLP, and LLM research and apply relevant techniques to ongoing projects. Lead and mentor junior data scientists in best practices for model development, validation, and deployment. Required Skills & Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. PhD preferred. Minimum of 5 years of hands-on experience in data science or applied machine learning. Strong proficiency in Python and related libraries such as NumPy, pandas, scikit-learn, TensorFlow, PyTorch, and spaCy. Demonstrated experience in NLP techniques and language model fine-tuning, including experience with Hugging Face Transformers or OpenAI APIs. Solid understanding of machine learning theory, model evaluation, and feature engineering. Experience working with cloud platforms such as AWS, GCP, or Azure for scalable model deployment. Familiarity with version control (Git), collaborative workflows, and agile development. Excellent communication skills with the ability to present complex technical concepts to diverse audiences. Strong analytical mindset with a focus on delivering measurable business outcomes. Nice to Have: Experience with vector databases (e.g., FAISS, Pinecone) and semantic search implementations. Familiarity with LLMOps, prompt engineering, and conversational AI systems. Experience in deploying and maintaining ML models in production environments

Gen AI Engineer Job Description Brightly Software is seeking a high performer to join our Product team in the role of Gen AI engineer to drive best in class client-facing AI features by creating and delivering insights that advise client decisions tomorrow. As a Gen AI Engineer, you will play a critical role in building AI offerings for Brightly. You will partner with our various software Product teams to drive client facing insights to inform smarter decisions faster. This will include the following: Design and implement applications powered by generative AI (e.g., LLMs, diffusion models), delivering contextual and actionable insights for clients. Establish best practices and documentation for prompt engineering, model fine-tuning, and evaluation to support cross-domain generative AI use cases. Build, test, and deploy generative AI applications using standard tools and frameworks for model inference, embeddings, vector stores, and orchestration pipelines. Key Responsibilities: Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector stores like Pinecone, FAISS, or AWS OpenSearch Develop GenAI applications using Hugging Face Transformers, LangChain, and Llama related frameworks Perform exploratory data analysis (EDA), data cleaning, and feature engineering to prepare data for model building. Design, develop, train, and evaluate machine learning models (e.g., classification, regression, clustering, natural language processing) with strong exerience in predictive and stastical modelling. Implement and deploy machine learning models into production using AWS services, with a strong focus on Amazon SageMaker (e.g., SageMaker Studio, training jobs, inference endpoints, SageMaker Pipelines). Understanding and development of state management workflows using Langraph. Engineer and evaluate prompts, including prompt chaining and output quality assessment Apply NLP and transformer model expertise to solve language tasks Deploy GenAI models to cloud platforms (preferably AWS) using Docker and Kubernetes Monitor and optimize model and pipeline performance for scalability and efficiency Communicate technical concepts clearly to cross-functional and non-technical stakeholders Thrive in a fast-paced, lean environment and contribute to scalable GenAI system design Qualifications Bachelor’s degree is required 2-4 years of experience of total experience with a strong focus on AI and ML and 1+ years in core GenAI Engineering Demonstrated expertise in working with large language models (LLMs) and generative AI systems, including both text-based and multimodal models. Strong programming skills in Python, including proficiency with data science libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and/or PyTorch. Familiarity with MLOps principles and tools for automating and streamlining the ML lifecycle. Experience working with agentic AI. Capable of building Retrieval-Augmented Generation (RAG) pipelines leveraging vector stores like Pinecone, Chroma, or FAISS. Strong programming skills in Python, with experience using leading AI/ML libraries such as Hugging Face Transformers and LangChain. Practical experience in working with vector databases and embedding methodologies for efficient information retrieval. Possess experience in developing and exposing API endpoints for accessing AI model capabilities using frameworks like FastAPI. Knowledgeable in prompt engineering techniques, including prompt chaining and performance evaluation strategies. Solid grasp of natural language processing (NLP) fundamentals and transformer-based model architectures. Experience in deploying machine learning models to cloud platforms (preferably AWS) and containerized environments using Docker or Kubernetes. Skilled in fine-tuning and assessing open-source models using methods such as LoRA, PEFT, and supervised training. Strong communication skills with the ability to convey complex technical concepts to non-technical stakeholders. Able to operate successfully in a lean, fast-paced organization, and to create a vision and organization that can scale quickly Senior Gen AI Engineer

💻 Internship Impact As a Software Engineer Intern, you’ll ship production code that impacts millions of users. You’ll be embedded in one of our core teams: Frontend: Build responsive UIs with React/TypeScript Backend: Scale microservices handling 10K+ RPS ML Infrastructure: Optimize recommendation systems Mobile: Enhance our iOS/Android apps 🔧 Key Projects ✔️ Develop features for creator monetization tool s✔️ Optimize API response times for feed loadi ng✔️ Implement real-time notifications using WebSock ets✔️ Contribute to our design system component lib r a ry 🛠 Tech Stack You’ll Use Frontend: React, Next.js, Gra phQLBackend: Node.js, Python , GoMobile: Swift, Kotlin, React Na tiveInfra: AWS, Kubernetes, R edisML: PyTorch, TensorFlow Ser v i ng 🎯 We’re Looking For Pursuing BS/MS in Computer Science or related f ieldProficiency in one modern language (JavaScript, Python, e tc.)Experience with web or mobile development (personal projects cou nt!)Strong problem-solving skills (LeetCode/CodeSignal is a p lus)Passion for building social prod u c ts ✨ Perks & Gr o wth Ownership: Deploy code to production We ek 1Mentorship: Paired with a senior engi neerLearning: $1K tech stipend for courses/b ooksFun: Team hackathons with $5K prize poolReturn Offers: 80% of interns receive FTE of fers

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connectR0126349bbc913121c9c10be393e180380695f30paypalStaff Software Engineer Your way to impact In this role, you’ll drive the adoption of Generative AI across PayPal’s Site Reliability Engineering organization by building intelligent, scalable platforms—like AI-powered chatbots and predictive systems—that enhance system reliability and engineering productivity. Your work will enable automation at scale, reduce operational toil, and deliver real-time insights that empower engineers across the business. As a technical leader in SRE Labs, you’ll shape how reliability engineering evolves at PayPal, influencing architecture, best practices, and product direction. You’ll be part of a collaborative, high-performance team that brings cutting-edge technology into mission-critical environments. Your day to day In your day to day role you will Lead the design and development of GenAI-driven platforms, including intelligent chatbots, AI copilots, and automation tools for Site Reliability use cases. Build and deploy machine learning models in production using technologies like Python, , LangChain, LLM APIs (OpenAI, Anthropic, Azure OpenAI), Collaborate cross-functionally with product, infrastructure, and SRE teams to translate reliability pain points into scalable AI/ML-powered solutions. Develop scalable front-end and backend services using React.js and Node.js to build user-facing AI-powered applications and APIs. Drive system design and architecture decisions that ensure scalability, reliability, and maintainability of AI platforms. Mentor engineers, share best practices, and help evolve PayPal’s GenAI strategy and engineering standards. What Do You Need To Bring- A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field—or equivalent practical experience. 8+ years of experience designing, developing, and deploying AI/ML solutions, with a strong emphasis on LLMs, chatbots, and scalable architecture. Proficiency in Python, React.js, and Node.js, with hands-on experience building scalable applications and services. Hands-on expertise with LangChain,,lang graph, RESTful APIs and cloud platforms including deploying models in production. Strong understanding of system design principles with experience architecting large-scale, fault-tolerant distributed systems. Solid knowledge of ML pipelines, prompt engineering, retrieval-augmented generation (RAG), and integration of LLMs with enterprise systems. A proven ability to lead cross-functional projects, mentor peers, and influence technical direction while working in Agile, fast-paced environments. You have good analytical and problem-solving skills. Strong verbal and written communication skills. Flexibility and willingness to learn new technologies and adapt quickly. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply. What you need to know about the role- SRE Labs, part of PayPal’s Site Reliability Engineering (SRE) organization, is seeking a Staff Software Engineer to lead and shape our Generative AI (GenAI) practice. In this high-impact role, you’ll architect and deliver scalable, production-grade AI solutions—ranging from intelligent chatbots to next-gen automation tools. You'll bring deep engineering expertise and a passion for AI innovation to transform how PayPal builds resilient and intelligent systems. This is a hands-on role with strategic reach: you’ll design, build, and lead AI-first platforms and services that redefine reliability engineering. You’ll work in a fast-paced, agile environment alongside top-tier engineers, product leads, and business partners to bring meaningful, customer-facing innovation to life. Meet our team PayPal SRE is a continuous engineering discipline that effectively combines software development and systems engineering to build and run scalable, distributed, fault-tolerant systems. The SRE team works together to ensure a continuous improvement to optimize for capacity and performance. SRE Labs enables innovation and builds enterprise-wide platforms to support Reliability.Chennai058a7c64f4a043ad9dc148854028f375IND-TNTNIN-TNc4f78be1a8f14da0ab49ce1162348a5eININD356600119bcdc9518960a01a46ac477aa2d240c99RECR_INTN001aacf3285c80f1001c4c166891c570000JF_Software_EngineeringFull_timehttps://paypal.eightfold.ai/careers?domain=paypal.com&sort_by=relevance&query=R0126349 The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you. We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply. The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Description Summary: We are looking for a talented Machine Learning Scientist to join our Venmo Data Science team, driving the development of AI-driven solutions that will shape the future of Venmo. You design and develop ML solutions including prediction, classification, clustering and recommendation.What you need to know about the role- SRE Labs, part of PayPal’s Site Reliability Engineering (SRE) organization, is seeking a Staff Software Engineer to lead and shape our Generative AI (GenAI) practice. In this high-impact role, you’ll architect and deliver scalable, production-grade AI solutions—ranging from intelligent chatbots to next-gen automation tools. You'll bring deep engineering expertise and a passion for AI innovation to transform how PayPal builds resilient and intelligent systems. This is a hands-on role with strategic reach: you’ll design, build, and lead AI-first platforms and services that redefine reliability engineering. You’ll work in a fast-paced, agile environment alongside top-tier engineers, product leads, and business partners to bring meaningful, customer-facing innovation to life. Meet our team PayPal SRE is a continuous engineering discipline that effectively combines software development and systems engineering to build and run scalable, distributed, fault-tolerant systems. The SRE team works together to ensure a continuous improvement to optimize for capacity and performance. SRE Labs enables innovation and builds enterprise-wide platforms to support Reliability. Job Description: With a strong background in Machine Learning and practical experience in building and implementing predictive models to solve business problems, you will help to bring insights and identify additional opportunities from Data & Machine Learning to market. Key Roles and Responsibilities include: Develop and implement advanced ML models, such as gradient boosted decision tree, LLMs, Clustering and deep learning models, to solve critical business problems related to Venmo. Design and deploy scalable ML/AI solutions that enhance Venmo's ability to provide a seamless customer experience, by working closely with our engineering group Communicate complex concepts and the results of models and analyses to both technical and non-technical audiences, influencing partners and customers with your insights and expertise. Basic Requirements: Masters degree or equivalent experience in a quantitative field (Computer Science, Mathematics, Statistics, Engineering, Artificial Intelligence, etc.) with 3+ yrs. of relevant industry experience or PhD with 2+ yrs. of relevant industry experience Great track record delivering solutions with attention to detail and efficiency Experience in any one of Product or Marketing domains is a big plus Proficient in Programming languages such as Python, SQL Fluent spoken and written English communication with business and engineering partners to exchange requirements, explain solution methodologies, and influence with insights Familiarity in relevant machine learning frameworks and packages such as Tensorflow and PyTorch. GCP/Hadoop and big data experience – an advantage Your way to impact In this role, you’ll drive the adoption of Generative AI across PayPal’s Site Reliability Engineering organization by building intelligent, scalable platforms—like AI-powered chatbots and predictive systems—that enhance system reliability and engineering productivity. Your work will enable automation at scale, reduce operational toil, and deliver real-time insights that empower engineers across the business. As a technical leader in SRE Labs, you’ll shape how reliability engineering evolves at PayPal, influencing architecture, best practices, and product direction. You’ll be part of a collaborative, high-performance team that brings cutting-edge technology into mission-critical environments. Your day to day In your day to day role you will Lead the design and development of GenAI-driven platforms, including intelligent chatbots, AI copilots, and automation tools for Site Reliability use cases. Build and deploy machine learning models in production using technologies like Python, , LangChain, LLM APIs (OpenAI, Anthropic, Azure OpenAI), Collaborate cross-functionally with product, infrastructure, and SRE teams to translate reliability pain points into scalable AI/ML-powered solutions. Develop scalable front-end and backend services using React.js and Node.js to build user-facing AI-powered applications and APIs. Drive system design and architecture decisions that ensure scalability, reliability, and maintainability of AI platforms. Mentor engineers, share best practices, and help evolve PayPal’s GenAI strategy and engineering standards. What Do You Need To Bring- A Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field—or equivalent practical experience. 8+ years of experience designing, developing, and deploying AI/ML solutions, with a strong emphasis on LLMs, chatbots, and scalable architecture. Proficiency in Python, React.js, and Node.js, with hands-on experience building scalable applications and services. Hands-on expertise with LangChain,,lang graph, RESTful APIs and cloud platforms including deploying models in production. Strong understanding of system design principles with experience architecting large-scale, fault-tolerant distributed systems. Solid knowledge of ML pipelines, prompt engineering, retrieval-augmented generation (RAG), and integration of LLMs with enterprise systems. A proven ability to lead cross-functional projects, mentor peers, and influence technical direction while working in Agile, fast-paced environments. You have good analytical and problem-solving skills. Strong verbal and written communication skills. Flexibility and willingness to learn new technologies and adapt quickly. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you. We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply. REQ ID R0126346R0126349

Summary Position Summary Quality Software Engineer (AI Automation) – CL4 Role Overview : As a Quality Engineer specializing in artificial intelligence (AI) and Generative AI (GenAI) technologies, you will actively engage in your quality engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users while also driving tangible value for Deloitte's business investments. You will leverage your quality engineering craftsmanship across multiple quality assurance disciplines and modern frameworks, consistently demonstrating your strong track record in delivering high-quality, outcome-focused solutions. The ideal candidate will have a background in quality assurance, test automation, and an understanding of AI and GenAI technologies. This role will be pivotal in enhancing our testing frameworks and ensuring the highest quality standards for our products. Key Responsibilities : Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop quality engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, AI-driven test automations. Technical Leadership and Advocacy: Serve as the quality advocate for products, ensuring high-quality automation coverage, appropriateness, feasibility, and alignment with business and customer goals. Design, develop, and maintain advanced automation frameworks to drive “Automation first mindset” using advanced techniques including BDD, AI and GenAI technologies to streamline and enhance the testing process. Engineering Craftsmanship: Maintain accountability for the integrity of test design, test automation, their ongoing maintenance and scale, as well as the quality of solutions. Stay hands-on, self-driven, and continuously learn new approaches, tools, techniques, and frameworks. Integrate AI and GenAI tools and techniques into existing testing processes to improve accuracy, efficiency, and coverage of automated tests. Customer-Centric Engineering: Develop lean quality engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions. Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, engineering, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation. Advanced Technical Proficiency: Possess basic knowledge of modern quality engineering practices and principles, including Agile methodologies and DevSecOps to deliver daily product deployments using techniques like fully automated in-sprint testing to accept the stories and work products, powered by AI/GenAI, throughout the SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate an understanding of the full lifecycle product development, focusing on continuous improvement and learning. Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs and UX/UI designs into test automation. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. Effective Communication and Influence: Exhibit strong communication skills, capable of articulating complex technical concepts clearly and compellingly. Support teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives. Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions. The team : US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes and leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Key Qualifications : A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. 5+ years of experience in quality assurance and test automation including coding the test scripts, with at least 1-2 years focused on AI and GenAI technologies. Hands-on experience with automation-first techniques like BDD and test automation tools like TOSCA, Selenium, Gherkin, Functionize, Testim, AccelQ. Experience with AI/GenAI tools and frameworks (e.g., TensorFlow, PyTorch, OpenAI, Python, etc.). Understanding of machine learning algorithms and their application in test automation. Experience with cloud hyper-scalers like Azure, AWS, and GCP. Good understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, ADO, GitHub, SonarQube, etc. Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care. How You will Grow: At Deloitte, our professional development plans focus on helping people at every level of their career to identify and use their strengths to do their best work every day and excel in everything they do. #CAP-PCJ Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India . Benefits To Help You Thrive At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Requisition code: 302790

Job Description Global Data Insight & Analytics organization is looking for a top-notch Software Engineer who has also got Machine Learning knowledge & Experience to add to our team to drive the next generation of AI/ML (Mach1ML) platform. In this role you will work in a small, cross-functional team. The position will collaborate directly and continuously with other engineers, business partners, product managers and designers from distributed locations, and will release early and often. The team you will be working on is focused on building Mach1ML platform – an AI/ML enablement platform to democratize Machine Learning across Ford enterprise (like OpenAI’s GPT, Facebook’s FBLearner, etc.) to deliver next-gen analytics innovation. We strongly believe that data has the power to help create great products and experiences which delight our customers. We believe that actionable and persistent insights, based on high quality data platform, help business and engineering make more impactful decisions. Our ambitions reach well beyond existing solutions, and we are in search of innovative individuals to join this Agile team. This is an exciting, fast-paced role which requires outstanding technical and organization skills combined with critical thinking, problem-solving and agile management tools to support team success. Responsibilities What you'll be able to do: As a Software Engineer, you will work on developing features for Mach1ML platform, support customers in model deployment using Mach1ML platform on GCP and On-prem. You will follow Rally to manage your work. You will incorporate an understanding of product functionality and customer perspective for model deployment. You will work on the cutting-edge technologies such as GCP, Kubernetes, Docker, Seldon, Tekton, Airflow, Rally, etc. Position Responsibilities: Work closely with Tech Anchor, Product Manager and Product Owner to deliver machine learning use cases using Ford Agile Framework. Work with Data Scientists and ML engineers to tackle challenging AI problems. Work specifically on the Deploy team to drive model deployment and AI/ML adoption with other internal and external systems. Help innovate by researching state-of-the-art deployment tools and share knowledge with the team. Lead by example in use of Paired Programming for cross training/upskilling, problem solving, and speed to delivery. Leverage latest GCP, CICD, ML technologies Critical Thinking: Able to influence the strategic direction of the company by finding opportunities in large, rich data sets and crafting and implementing data driven strategies that fuel growth including cost savings, revenue, and profit. Modelling: Assessments, and evaluating impacts of missing/unusable data, design and select features, develop, and implement statistical/predictive models using advanced algorithms on diverse sources of data and testing and validation of models, such as forecasting, natural language processing, pattern recognition, machine vision, supervised and unsupervised classification, decision trees, neural networks, etc. Analytics: Leverage rigorous analytical and statistical techniques to identify trends and relationships between different components of data, draw appropriate conclusions and translate analytical findings and recommendations into business strategies or engineering decisions - with statistical confidence Data Engineering: Experience with crafting ETL processes to source and link data in preparation for Model/Algorithm development. This includes domain expertise of data sets in the environment, third-party data evaluations, data quality Visualization: Build visualizations to connect disparate data, find patterns and tell engaging stories. This includes both scientific visualization as well as geographic using applications such as Seaborn, Qlik Sense/PowerBI/Tableau/Looker Studio, etc. Qualifications Minimum Requirements we seek: Bachelor’s or master’s degree in computer science engineering or related field or a combination of education and equivalent experience. 3+ years of experience in full stack software development 3+ years’ experience in Cloud technologies & services, preferably GCP 3+ years of experience of practicing statistical methods and their accurate application e.g. ANOVA, principal component analysis, correspondence analysis, k-means clustering, factor analysis, multi-variate analysis, Neural Networks, causal inference, Gaussian regression, etc. 3+ years’ experience with Python, SQL, BQ. Experience in SonarQube, CICD, Tekton, terraform, GCS, GCP Looker, Google cloud build, cloud run, Vertex AI, Airflow, TensorFlow, etc., Experience in Train, Build and Deploy ML, DL Models Experience in HuggingFace, Chainlit, Streamlit, React Ability to understand technical, functional, non-functional, security aspects of business requirements and delivering them end-to-end. Ability to adapt quickly with opensource products & tools to integrate with ML Platforms Building and deploying Models (Scikit learn, DataRobots, TensorFlow PyTorch, etc.) Developing and deploying On-Prem & Cloud environments Kubernetes, Tekton, OpenShift, Terraform, Vertex AI Our Preferred Requirements: Master’s degree in computer science engineering, or related field or a combination of education and equivalent experience. Demonstrated successful application of analytical methods and machine learning techniques with measurable impact on product/design/business/strategy. Proficiency in programming languages such as Python with a strong emphasis on machine learning libraries, generative AI frameworks, and monitoring tools. Utilize tools and technologies such as TensorFlow, PyTorch, scikit-learn, and other machine learning libraries to build and deploy machine learning solutions on cloud platforms. Design and implement cloud infrastructure using technologies such as Kubernetes, Terraform, and Tekton to support scalable and reliable deployment of machine learning models, generative AI models, and applications. Integrate machine learning and generative AI models into production systems on cloud platforms such as Google Cloud Platform (GCP) and ensure scalability, performance, and proactive monitoring. Implement monitoring solutions to track the performance, health, and security of systems and applications, utilizing tools such as Prometheus, Grafana, and other relevant monitoring tools. Conduct code reviews and provide constructive feedback to team members on machine learning-related projects. Knowledge and experience in agentic workflow based application development and DevOps Stay up to date with the latest trends and advancements in machine learning and data science.

Overview: AI Automation Engineer to design, develop, and implement intelligent automation solutions. This role involves leveraging AI, machine learning, and automation tools to streamline workflows, optimize business processes, and enhance operational efficiency. You will work closely with cross-functional teams to integrate AI-powered automation into enterprise systems. Responsibilities: Design and develop AI-driven automation solutions to optimize workflows and business operations. Implement machine learning models and AI algorithms to enhance process automation. Develop and maintain automation scripts, bots, and AI-based workflows. Integrate AI automation with existing systems, APIs, and databases. Utilize RPA (Robotic Process Automation) tools such as UiPath, Automation Anywhere, or Blue Prism . Work with cloud-based AI services (AWS AI/ML, Google AI, Azure AI) to deploy scalable automation solutions. Monitor automation performance, troubleshoot issues, and optimize efficiency. Ensure automation security, compliance, and governance best practices. Stay updated with advancements in AI, ML, and automation technologies. Qualifications: 9+ years of experience with 6+ years of experience in AI, automation, or RPA development. Strong programming skills in Python, Java, or JavaScript. Hands-on experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-Learn). Expertise in RPA tools (UiPath, Automation Anywhere, Blue Prism). Experience with workflow automation tools (Apache Airflow, Zapier, Power Automate). Proficiency in RESTful APIs, microservices, and cloud platforms (AWS, GCP, Azure). Knowledge of database technologies (SQL, NoSQL) for AI-driven automation. Strong understanding of DevOps, MLOps, and CI/CD pipelines. Preferred Qualifications Experience with AI chatbots and virtual assistants (Dialogflow, Rasa, OpenAI GPT). Exposure to computer vision and NLP for intelligent automation. Knowledge of vector databases for AI-powered search. Familiarity with enterprise automation tools (ServiceNow, Workato, Alteryx).

8+ years of total experience with 5+ years of professional experience in AI, ML or a related field. Master's or PhD in Computer Science, Mathematics, AI or a related field. Good mathematical understanding of machine learning and deep learning algorithms. Advanced knowledge of statistical and algorithmic models as well as of fundamental mathematical concepts, such as linear algebra and probability. Experience with Natural Language Processing, Deep Learning, and Computer Vision techniques. Proficiency in programming languages such as Python or Scala, along with experience using DL frameworks like TensorFlow, PyTorch etc. Experience working with large data sets and writing efficient code capable of processing large data streams at speed. Experience in program leadership, governance, and change enablement Understand client challenges and propose solutions based on AI/GenAI capabilities. Analyze and explain AI and machine learning (ML) solutions while setting and maintaining high ethical standards. Work on functional design, process design, prototyping, testing, training, and defining support procedures, in collaboration with data engineering team and executive leadership. Train and deploy AI models to solve complex business problems or automate processes. Convert AI/ML models into APIs to be used in other applications. Manage a team in implementing AI solutions and developing products. Collaborate with external partners, such as research institutions or universities, to explore innovative AI approaches and foster collaborative research projects. Ensure compliance with data privacy regulations and ethical guidelines while working with sensitive and confidential data. Stay up to date with the latest developments in machine learning and AI. Experience working with Azure Data & AI services. Experience with MLOps tools like MLFLow, Azure MLOps or similar tools. High level of ownership and creative problem solving under resource constraints. Excellent verbal and written communication skills. Ability to interact with C-Level executives

Quality Software Engineer (AI Automation) – CL4 Role Overview : As a Quality Engineer specializing in artificial intelligence (AI) and Generative AI (GenAI) technologies, you will actively engage in your quality engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users while also driving tangible value for Deloitte's business investments. You will leverage your quality engineering craftsmanship across multiple quality assurance disciplines and modern frameworks, consistently demonstrating your strong track record in delivering high-quality, outcome-focused solutions. The ideal candidate will have a background in quality assurance, test automation, and an understanding of AI and GenAI technologies. This role will be pivotal in enhancing our testing frameworks and ensuring the highest quality standards for our products. Key Responsibilities : Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop quality engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, AI-driven test automations. Technical Leadership and Advocacy: Serve as the quality advocate for products, ensuring high-quality automation coverage, appropriateness, feasibility, and alignment with business and customer goals. Design, develop, and maintain advanced automation frameworks to drive “Automation first mindset” using advanced techniques including BDD, AI and GenAI technologies to streamline and enhance the testing process. Engineering Craftsmanship: Maintain accountability for the integrity of test design, test automation, their ongoing maintenance and scale, as well as the quality of solutions. Stay hands-on, self-driven, and continuously learn new approaches, tools, techniques, and frameworks. Integrate AI and GenAI tools and techniques into existing testing processes to improve accuracy, efficiency, and coverage of automated tests. Customer-Centric Engineering: Develop lean quality engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions. Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, engineering, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation. Advanced Technical Proficiency: Possess basic knowledge of modern quality engineering practices and principles, including Agile methodologies and DevSecOps to deliver daily product deployments using techniques like fully automated in-sprint testing to accept the stories and work products, powered by AI/GenAI, throughout the SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate an understanding of the full lifecycle product development, focusing on continuous improvement and learning. Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs and UX/UI designs into test automation. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. Effective Communication and Influence: Exhibit strong communication skills, capable of articulating complex technical concepts clearly and compellingly. Support teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives. Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions. The team : US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes and leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. Key Qualifications : § A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor. § 5+ years of experience in quality assurance and test automation including coding the test scripts, with at least 1-2 years focused on AI and GenAI technologies. § Hands-on experience with automation-first techniques like BDD and test automation tools like TOSCA, Selenium, Gherkin, Functionize, Testim, AccelQ. § Experience with AI/GenAI tools and frameworks (e.g., TensorFlow, PyTorch, OpenAI, Python, etc.). § Understanding of machine learning algorithms and their application in test automation. § Experience with cloud hyper-scalers like Azure, AWS, and GCP. § Good understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, ADO, GitHub, SonarQube, etc. § Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care. How You will Grow: At Deloitte, our professional development plans focus on helping people at every level of their career to identify and use their strengths to do their best work every day and excel in everything they do. #CAP-PCJ Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India. Benefits to help you thrive At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Requisition code: 302790

JOB DESCRIPTION AI Lead - Innovation & Product Development About Us KPMG is a dynamic and forward-thinking Professional service firm committed to leveraging cutting-edge artificial intelligence to create transformative products and solutions. We are building a team of passionate innovators who thrive on solving complex challenges and pushing the boundaries of what's possible with AI. Job Summary We are seeking an experienced and visionary AI Lead to spearhead our AI innovation and product development. The ideal candidate will be a hands-on leader with a strong background in solution architecture, a proven track record in developing AI-based products, and deep expertise in Generative AI applications, including Agentic AI. This role requires a comprehensive understanding of AI models, frameworks, and Agentic AI, along with exposure to GPU infrastructure, to design, build, and deploy scalable AI solutions. You will drive our AI strategy, lead cross-functional teams, and transform complex ideas into tangible, market-ready products, with a strong understanding of enterprise requirements from a professional services perspective. Key Responsibilities Strategic Leadership & Innovation: o Define and drive the AI innovation roadmap, identifying emerging trends in AI, Generative AI and Agentic AI. o Lead research, evaluation, and adoption of new AI models, algorithms, and frameworks. o Foster a culture of continuous learning, experimentation, and innovation. AI Product Development & Management: o Lead end-to-end development of AI-based products, from ideation to deployment and optimization. o Collaborate with product managers, designers, and stakeholders to translate business requirements into viable AI solutions. o Ensure successful delivery of high-quality, scalable, and performant AI products. o Client Engagement & Solutioning: Work with multiple clients to understand requirements, design tailored AI solutions, develop proofs-of-concept (POCs), and ensure successful implementation in a professional services context. Solution Architecture & Design: o Design robust, scalable, and secure AI solution architectures across multi-cloud platforms and on-premise infrastructure. o Provide technical guidance and architectural oversight for AI initiatives, focusing on optimizing for GPU infrastructure . o Evaluate and recommend AI technologies, tools, and infrastructure, including Large Language Models (LLMs) and Small Language Models (SLMs) on cloud and on-premise. Team Leadership & Mentorship: o Lead, mentor, and grow a team of talented AI engineers, data scientists, and machine learning specialists. o Conduct code reviews and ensure adherence to coding standards and architectural principles. o Promote collaboration and knowledge sharing. Technical Expertise & Implementation: o Hands-on experience in developing and deploying Generative AI applications (e.g., LLMs, RAG, GraphRags , image generation, code generation), including Agentic AI and Model Context Protocol (MCP). o Proficiency with Agentic AI orchestration frameworks such as LangChain, LlamaIndex, and/or similar tools. o Experience with leading LLM providers and models including OpenAI, Llama, Anthropic, and others. o Familiarity with AI-powered tools and platforms such as Microsoft Copilot, GitHub Copilot etc. o Strong understanding of various machine learning models (deep learning, supervised, unsupervised, reinforcement learning). o Experience with large datasets, ensuring data quality, feature engineering, and efficient data processing for AI model training. o Deep understanding of GPU infrastructure, for AI model training or/ and inference. Qualifications Bachelor's or Master's degree in Computer Science, AI, ML, Data Science, or a related quantitative field. 8+ years in AI/ML development, with at least 3 years in a leadership or lead architect role. Mandatory: Proven experience in leading the development and deployment of AI-based products and solutions. Mandatory: Extensive hands-on experience with Generative AI models and frameworks (e.g., TensorFlow, PyTorch, Hugging Face, OpenAI APIs, etc.), including practical application of Agentic AI. Proficiency with Agentic AI orchestration frameworks such as LangChain, LlamaIndex, and/or similar tools. Experience in leveraging and integrating various LLM providers and models, including but not limited to OpenAI, Llama, and Anthropic. Familiarity with AI-powered development tools and platforms such as Microsoft Copilot, GitHub Copilot, and other code generation/assistance tools. Strong understanding of solution architecture principles for large-scale AI systems, including multi-cloud platforms and on-premise deployments. Mandatory: Exposure to and understanding of GPU infrastructure, especially NVIDIA, for AI workloads. Experience with Large Language Models (LLMs) and Small Language Models (SLMs) on both cloud and on-premise environments. Proficiency in programming languages such as Python, with strong software engineering fundamentals. Familiarity with MLOps practices, including model versioning, deployment, monitoring, and retraining. Mandatory: Demonstrated industry exposure to professional services, with a proven track record of working with multiple clients to solution requirements, conduct POCs, and understand enterprise-level needs. Excellent communication, interpersonal, and presentation skills, with the ability to articulate complex technical concepts to diverse audiences. Strong problem-solving abilities and a strategic mindset. What We Offer Opportunity to work on cutting-edge AI technologies and shape the future of our products. A collaborative and innovative work environment. Competitive salary and benefits package. Professional development and growth opportunities. The chance to make a significant impact on our business and our customers. If you are a passionate AI leader with a drive for innovation and a desire to build groundbreaking AI products, we encourage you to apply!